Agentic AI, engineered to scale.
rhoIQ architects, builds, and operates agentic systems on top of LLMs and retrieval — evaluated, observable, and dependable for the teams and workloads that rely on them.
Two ways we engage
- RAG, agent, and LLM architecture — from data pipeline to UX
- Eval harnesses, regression gates, and online observability
- Model selection, fine-tuning, distillation, and cost/latency tuning
- AI strategy, roadmap reviews, and technical due diligence
- Safety, evals, and red-team workflows for regulated domains
- Full-stack AI products built from spec to launch
- Auth, payments, data, and infrastructure designed for scale
- ML ops: deployment, monitoring, evaluation, and continuous improvement
- Documentation, runbooks, and handoff — or ongoing operation
Some of what our team builds and operates
Multi-channel engagement platform for SMBs. Two-way SMS with AI-assisted reply drafting and audience segmentation, an AI voice agent that handles inbound and outbound calls end-to-end, and an agentic AI video-monitoring layer that watches camera feeds, reasons over events, and triggers alerts and actions.
A live platform that helps homeowners challenge over-assessed valuations. Combines comparable-sales retrieval, structured evidence generation, and an evaluated LLM pipeline that produces hearing-ready protest packets.
An applied-AI company that puts a team on any problem.
rhoIQ partners with teams that need AI built for real-world constraints — latency, cost, accuracy, safety, and the messy reality of live data. Our people come from engineering, research, and product backgrounds, and we go deep on the parts of the stack most teams underinvest in: evaluation, retrieval quality, observability, and the operational discipline that keeps AI trustworthy over time.
Whatever the problem, we can put a full team on it — engineering, research, and product — and own the work end to end, from architecture and build through launch and ongoing operation.
- Applied research — frontier model evaluation, fine-tuning, distillation
- Retrieval engineering — hybrid search, re-ranking, structured RAG over messy data
- Agentic systems — tool use, planning, multi-step workflows with guardrails
- Eval & observability infrastructure — offline benchmarks, online tracing, regression gates
- Full-stack delivery — apps, auth, payments, infrastructure, and ML ops
- Dedicated teams — cross-functional pods of engineers, researchers, and product
Tell us what you're building.
Send a short brief and we'll get back within one business day to scope a conversation. Prefer email? Reach the team directly.
info@rhoiq.com